FuboTV Inc.: operating expenses

What this measure means

Recurring operating costs under this accounting concept, generally excluding production costs included in cost of sales. Check filing presentation before combining expense subtotals.

Exact concept: us-gaap:OperatingExpenses. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2011-01-01 to 2024-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Related financial histories

• FuboTV Inc.: total assets
• FuboTV Inc.: total liabilities
• FuboTV Inc.: stockholders equity
• FuboTV Inc.: cash and cash equivalents
• FuboTV Inc.: net income or loss
• FuboTV Inc.: operating cash flow
• FuboTV Inc.: capital expenditure payments
• FuboTV Inc.: revenue
• FuboTV Inc.: contract revenue excluding tax
• FuboTV Inc.: financing cash flow
• FuboTV Inc.: investing cash flow
• FuboTV Inc.: retained earnings or deficit
• FuboTV Inc.: basic weighted-average shares
• FuboTV Inc.: diluted weighted-average shares
• FuboTV Inc.: basic earnings per share
• FuboTV Inc.: diluted earnings per share
• FuboTV Inc.: income tax expense or benefit
• FuboTV Inc.: net property, plant and equipment
• FuboTV Inc.: share-based compensation expense
• FuboTV Inc.: operating income or loss
• FuboTV Inc.: current assets
• FuboTV Inc.: interest expense
• FuboTV Inc.: current liabilities
• FuboTV Inc.: current accounts payable
• FuboTV Inc.: goodwill carrying amount
• FuboTV Inc.: net finite-lived intangible assets
• FuboTV Inc.: net current accounts receivable
• FuboTV Inc.: gross profit
• FuboTV Inc.: research and development expense

Inspect the source

Entity

FuboTV Inc. / CIK 0001484769

Captured

2026-09-20T09:09:21.587Z

SEC response SHA-256

ea10a688894936583797d7b152d6f44f1e825c45722945cc4cad36269ce3fc7a

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

• Get an API key and run your first validation
• Connect the MCP server to your coding assistant
• Inspect the ALPHAC engine on GitHub
• Read the MCP server source and integration examples

import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001484769.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))